Data Engineer; Mid-Level

Fully Remote | Technology Development | Starting $115,000

We are seeking a mid-level Data Engineer to help build and scale the data platform that powers analytics, business intelligence, machine learning, and customer-facing products across our organization. This role focuses on building reliable, high-performance data pipelines and modern data architectures that make our data trusted, accessible, and actionable.

The ideal candidate has 2-3 years of hands‑on data engineering experience, strong SQL and Python skills, and working experience with modern cloud data platforms. Just as importantly, this person already builds with AI, using AI coding assistants in day‑to‑day development and understanding how LLMs and ML services fit into a modern data platform. You do not need to be an ML engineer.

You do need AI tooling to be part of how you already work, and you need the judgment to know when its output is wrong.

This individual will partner with Product, Engineering, Business Intelligence, Data Science, and business stakeholders to deliver data solutions that support operational, analytical, and AI‑driven initiatives.

This is a full‑time, salaried, remote position. Candidate must reside within the Continental U.S. Eastern or Central time zones highly preferred, but all are welcome to apply who can support 8:30AM-5:30PM eastern hours.

• Build and maintain scalable data pipelines and ELT/ETL workflows.
• Develop and optimize data models and data structures that support reporting, analytics, machine learning, and operational applications.
• Use Snowflake and modern cloud data platforms to ingest, transform, and optimize large datasets.
• Partner with Business Intelligence and Data Science teams to deliver trusted, production‑ready datasets.
• Build and maintain the data foundations that AI and ML workloads depend on; clean, well‑documented, well‑governed datasets and feature tables.
• Implement data quality, validation, and monitoring processes.
• Support both batch and near real‑time data integration requirements.
• Contribute to APIs and data services that enable internal and customer‑facing applications.
• Use AI coding assistants to accelerate development, while owning and validating everything that ships under your name.
• Improve data pipeline performance, scalability, and cost efficiency.
• Document data architectures, pipeline processes, and engineering standards.
• Participate in code and design reviews and help uphold engineering best practices.

• 2–3 years of experience in Data Engineering, Software Engineering, or a related field (internships and co‑ops count toward this).
• Strong SQL skills and hands‑on experience with a modern cloud data platform, preferably Snowflake.
• Solid proficiency with Python and Sound Software Development Practices.
• Experience building and maintaining ELT/ETL pipelines.
• Working understanding of data modeling and data warehousing concepts.
• Experience integrating structured and semi‑structured data from multiple sources.
• Familiarity with data orchestration and transformation frameworks.
• Working knowledge of version control (Git) and branch‑based collaboration.
• Strong troubleshooting instincts and a desire to become a world‑class data and SQL debugger.
• Clear written and verbal communication, and the ability to work independently in a remote‑first environment.

• Daily working use of at least one AI coding assistant (Claude Code, Git Hub Copilot, Cursor, or similar) for writing, refactoring, debugging code and the judgment to recognize when its output is wrong.
• Practical prompt‑writing ability: can break a real task into clear, scoped instructions and iterate toward a correct result rather than accepting the first answer.
• Conceptual understanding of how LLMs work at…